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Featured researches published by Yongzhen Zhang.


Tribology Transactions | 2010

Comparative Study on Wear Behaviors of Metal-Impregnated Carbon Material and C/C Composite Under Electrical Sliding

Bao Shangguan; Yongzhen Zhang; Jiandong Xing; Lemin Sun; Yun Chen

In this article, the wear behavior of metal-impregnated carbon materials (MIC) and carbon–carbon composites(C-C) was investigated using a self-made current-carrying wear tester producing an electrical current of 40–160 A and a contact speed of 10–50 m/s. The worn surfaces were observed by means of scanning electron microscopy (SEM), and a new parameter for current-carrying stability that describes the stability of the current as a function of wear was proposed. The results indicate that the wear rate of both materials tested increased with either an increase in electrical current or contact sliding speed. Compared to the metal-impregnated carbon material, the C-C composite material not only displayed superior wear resistance but superior current-carrying stability as well. With increasing electrical current, the current-carrying stability of the two materials changed within a narrow range at a speed of 20 m/s and decreased at a speed of 50 m/s. Wear failure was mainly due to electrical erosion occurring at high speed and high current.


Tribology Transactions | 2014

The Study of Arc Rate, Friction, and Wear Performance of C/C Composites in Pantograph–Catenary System

Huijie Zhang; Lemin Sun; Yongzhen Zhang; Bao Shangguan

A series of tests on arc rate, friction coefficient, and wear rate of electrical current collectors sliding against overhead contact wires under different conditions was carried out on a high-speed friction and wear testing machine with a pin-on-disc configuration. The worn surface morphology and composition were examined using a scanning electron microscope and energy dispersion spectrum analyzer, respectively. The effects of current, velocity, and load on the arc rate, friction coefficient, and wear rate of C/C composites/QCr0.5 couples were investigated, and the influence mechanism of test parameters on C/C composites was explained. It is concluded that the wear rate increases with an increase in current and velocity and has a decreasing trend with the increase in load. The friction coefficient increases with an increase in velocity and load. The arc rate of C/C composites/QCr0.5 couples increases with an increase in current and velocity. Under the condition of the same current and velocity, when the load is 70 N, the arc rate is the lowest.


STLE/ASME 2010 International Joint Tribology Conference | 2010

Tribo-Electric Behaviors of Copper Under Dry Sliding Against Cu-Cr Alloys

Bao Shangguan; Yongzhen Zhang; Jiandong Xing

The tribological and electrical conduction behaviors of copper under dry sliding against copper-chromium alloys were investigated on the basis of simulation tests. The experimental results show that electrical current and trbological parameters have combined effects on both electrical conduction ability and trological properties. High sliding velocity and electrical current density deteriorate both the tribological and electrical conduction properties in tribo-electrical sliding system. In the end, Worn surface analysis suggests frictional and electrical resistance heating, electrical arc spoiling are the main factors to influence the tribological and electrical conduction properties.Copyright


World Tribology Congress III, Volume 1 | 2005

Artificial Neural Network and Genetic Algorithms for Discontinuously Reinforced Aluminum Composites Frictional Behaviour Prediction

Ming Qiu; Yongzhen Zhang; Jun Zhu

By using genetic algorithms and radius basis function (GARBF) neural network, the predicting model of friction coefficient has been established based on a measured database with five sliding velocities of 40, 55, 70, 85, 100 m/s and four different normal pressures of 0.1333, 0.4667, 0.60 and 0.7333 MPa. The modeling results confirm the feasibility of the GARBF network and its good correlation with the experimental results. The predictive quality of the GARBF network can be further improved by enlarging the training datasets and by optimizing the network construction. A well-trained GARBF modeling is expected to be very helpful for selecting composite component under different working conditions, and for predicting tribological properties. Finally, by using GARBF modeling data to predict analysis, the results show that the friction coefficients of these composites were increased with the increase in material thermal capability at some region.Copyright


Archive | 2010

Magnetic field control device for friction and abrasion test

Yue Chen; Ming Qiu; Jian Shang; Bao Shangguan; Xishun Tie; Yongzhen Zhang; Zhanli Zhang


Archive | 2010

Multiple atmosphere proportion accurate control device for friction wear testing machine

Ming Qiu; Yongzhen Zhang; Xishun Tie; Wenzheng Yuan


Archive | 2008

Water mist cooling experiment device

Yongzhen Zhang; Guanbao Shang; Sanming Du; Ming Qiu; Xishun Tie; Lemin Sun


Tsinghua Science & Technology | 2004

Fractal characteristics of dry sliding surfaces based on 3-D measurements

Yongzhen Zhang; Lemin Sun; Weimin Liu; Jun Zhu; Bao Shangguan


Archive | 2011

Regulation test method for friction temperature, and pin sample for the same

Xishun Tie; Sanming Du; Ming Qiu; Yue Chen; Yongzhen Zhang


Archive | 2008

Cast exudation process of investment casting mould

Yue Chen; Yongzhen Zhang; Bao Shangguan; Xishun Tie; Lemin Zhang; Sanming Du; Ming Qiu

Collaboration


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Bao Shangguan

Henan University of Science and Technology

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Ming Qiu

Xi'an Jiaotong University

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Xishun Tie

Henan University of Science and Technology

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Lemin Sun

Henan University of Science and Technology

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Yue Chen

Henan University of Science and Technology

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Sanming Du

Henan University of Science and Technology

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Jiandong Xing

Xi'an Jiaotong University

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Jun Zhu

Xi'an Jiaotong University

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Huijie Zhang

Henan University of Science and Technology

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Weimin Liu

Chinese Academy of Sciences

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